The operator is required to be constantly vigilant and even more attentive when operating the device. The paper introduces a cooperation of a car simulator realized in the virtual reality (VR) environments and measurements of "human driver behavior" focused mainly on the aspects of HMI and drivers' attention decrease. In the first part a conception and a development of our VR car simulation devices are described. During the development of the car simulators many problems need to be solved. One of these problems is represented by a simplification and a partial automation of a scenery creation. The first part is dedicated to the algorithms used in our tools, which help to automate the creation of virtual scenes. The next part analyses, in greater detail, the tools themselves and the rest of this section deals with demonstration of the scenes, which were modeled using these tools. For simpler and faster generation of virtual sceneries it is suitable to store the models within a hierarchical database 3D object. Our database includes model objects from which it subsequently forms surroundings for the road virtual scenes. In the article is described how to specify the 3D model properties - their fundamental characteristic and consequent differentiation into specific categories. Sound perception cues are one of the most important ones besides the visual cues in the car simulation. The audio section of this article deals with simulating a sound of a car engine as a most significant audio stimulant for the driver. It shows the basics of the cross fading system which renders the car audio from multiple looped samples. The first part contains an analysis of car engine sound, the second part describes how to synthesize it on the computer. Validation measurements and consequent results are shown at the end of this section. The final paragraphs show examples of experiments developed for measurements of the driver's fatigue and other aspects of the driver's behavior.
The paper technically describes the principles of incorporation of the biofeedback system into the system of a driving simulator. After a brief introduction of the basic features of EEG biofeedback, the most important scenarios where such simulator enhancement can be successfully used are described. The system is introduced with the use of an analysis of the major technical and construction aspects, such as the software design, hardware realization and its incorporation into the driving simulator system. Finally, the paper sketches pilot experiments which were performed using EEG biofeedback incorporated into the driving simulator.
This paper introduces the cooperation of a virtual car simulator and
EEG measurements to test a human driver’s behavior in demanding situations. After a short explanation of the main principles and tasks of EEG measurements, basic concepts of our experiments are presented. The following part is devoted to problems and solutions concerning the physical model, graphical and other aspects of our simulator. At the end of the article various measuring procedures are presented.
The paper summarizes the first results of an identification of sleepy state of drivers using a complex set of outputs from simulated driving. The driving information, such as deviation from the centerline of the road and the steering wheel position as well as two-point EEG, was used. The process consists of the preprocessing of data, in fact a transformation into a form proper for classification, and a classification into one of two classes, i.e. wakefulness and drowsiness. There were two groups of drivers submitted to tests, the wakeful ones, and the drivers after serious sleep deprivation. We found that it is possible to distinguish these groups using an appropriate classifier with some rather substantial error, which can possibly be tackled by using an apt methodology.